DBMS > Couchbase vs. HBase vs. Hive vs. Oracle vs. Yaacomo

System Properties Comparison Couchbase vs. HBase vs. Hive vs. Oracle vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Wide-column store based on Apache Hadoop and on concepts of BigTable

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Widely used RDBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Wide column store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

www.couchbase.com

hbase.apache.org

hive.apache.org

www.oracle.com/database

yaacomo.com

Technical documentation

docs.couchbase.com

hbase.apache.org/book.html

cwiki.apache.org/confluence/display/Hive/Home

docs.oracle.com/en/database

Developer

Couchbase, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

initially developed by Facebook

Oracle

Q2WEB GmbH

Initial release

2011

2008

2012

1980

2009

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

2.3.4, January 2021

3.1.3, April 2022

23c, September 2023

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache version 2

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

Java

C and C++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Android
Linux
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Java
PHP
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Coprocessors in Java

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Single row ACID (across millions of columns)

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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